https://doi.org/10.4081/aiua.2026.15133
Diagnostic performance of PI-RADS and PSA density for detecting clinically significant prostate cancer
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Published: 29 June 2026
Background: Multiparametric magnetic resonance imaging (mpMRI), interpreted using the Prostate Imaging Reporting and Data System (PI-RADS), is increasingly used to improve prostate cancer detection and reduce unnecessary biopsies. However, its diagnostic accuracy compared with histopathological confirmation remains variable across institutions. This study aimed to evaluate the correlation between mpMRI findings and TRUS-guided prostate biopsy results in detecting clinically significant prostate cancer (csPCa) in our patient cohort.
Methods: This retrospective diagnostic accuracy study included 100 biopsy records (86 unique patients) who underwent mpMRI followed by TRUS-guided biopsy. mpMRI findings were scored using PI-RADS v2, while biopsy histopathology served as the reference standard. Clinically significant prostate cancer (csPCa) was defined as ISUP Grade Group ≥ 2. Diagnostic performance was assessed for two interpretive rules: (1) Baseline rule: PI-RADS ≥ 4 as positive; (2) Combined rule: PIRADS ≥ 4 or PI-RADS = 3 with PSA density (PSAD) > 0.15 ng/mL/mL. Sensitivity, specificity, predictive values, and area under the RoC curve (AUC) were calculated. Hierarchical logistic regression assessed the independent contribution of PSAD and clinical covariates.
Results: Malignant cases showed higher PSA (median 10.0 ng/mL vs 7.0 ng/mL) and PSAD (0.32 vs 0.13 ng/mL/mL) and smaller prostate volumes (36.5 mL vs 61.0 mL) compared with benign cases. csPCa detection increased with rising PI-RADS category (3.7% for PI-RADS 3, 56.9 % for PI-RADS 4-5). At the patient level, the Baseline rule achieved sensitivity = 86.7% and specificity = 66.1%, while the Combined rule increased sensitivity to 90.0 % with specificity = 55.4%. The ordinal PI-RADS score demonstrated excellent discrimination (AUC = 0.826, 95% CI 0.713-0.924). In logistic regression, adding PSAD improved model AUC from 0.836 to 0.888 (p < 0.001), and inclusion of age and prostate volume further increased AUC to 0.900 (p = 0.044). within PI-RADS 3 lesions, the optimal PSAD threshold (youden index) was 0.163 ng/mL/mL, yielding 100% sensitivity and 76% specificity. Postbiopsy complications were within expected ranges, with mild hematuria (29%), minor rectal bleeding (23%), and UTI (7%) being most common.
Conclusions: mpMRI findings strongly correlated with histopathological outcomes from TRUS-guided biopsy. Incorporating PSA density significantly enhanced the diagnostic accuracy for csPCa, particularly in equivocal PI-RADS 3 cases. Combining mpMRI and PSAD can refine patient selection for biopsy and improve early detection of clinically significant prostate cancer.
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1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2018. CA Cancer J Clin. 2018; 68:7-30.
2. Zhu M, Liang Z, Feng T, et al. Up-to-date imaging and diagnostic techniques for prostate cancer: A literature review. Diagnostics. 2023; 13:2283.
3. Hodge KK, McNeal JE, Terris MK, Stamey TA. Random systematic versus directed ultrasound-guided transrectal core biopsies of the prostate. J Urol. 1989; 142:71-4.
4. Ortner G, Tzanaki E, Rai BP, et al. Transperineal prostate biopsy: the modern gold standard. Turk J Urol. 2021; 47(Suppl 1):S19-25.
5. Rebez G, Barbiero M, Simonato FA, et al. Targeted prostate biopsy: How, when, and why? Diagnostics. 2024; 14:1864.
6. Shaw GL, Thomas BC, Dawson SN, et al. Identification of pathologically insignificant prostate cancer is not accurate in unscreened men. Br J Cancer. 2014; 110:2405-11.
7. Abraham NE, Mendhiratta N, Taneja SS. Patterns of repeat prostate biopsy in contemporary practice. J Urol. 2015; 193:1178-84.
8. Turkbey B, Brown AM, Sankineni S, et al. Multiparametric prostate MRI in PCa. CA Cancer J Clin. 2016; 66:326-36.
9. Patel NU, Lind KE, Garg K, et al. Assessment of PI-RADS ≥3 for diagnosing csPCa. Abdom Radiol. 2019; 44:705-12
10. Yamashiro JR, de Riese WT. Prostate volume vs cancer incidence: 30-year review. Res Rep Urol. 2021; 13:749-57.
11. Li W, Shang W, Lu F, et al. Diagnostic performance of EPE grading system. Front Oncol. 2022; 11:792120.
12. Jiang S, Li Y, Guo Y, et al. MRI-measured periprostatic fat ratio as risk factor. Sci Rep. 2024; 14:20896.
13. Liu WQ, Wei Y, Ke ZB, et al. MRI radiomics predicting pathological upgrading. Acad Radiol. 2024.
14. Kızılay F, Çelik S, Sözen S, et al. PI-RADS correlation with RP pathology: multicenter study. Prostate Int. 2020; 8:10-15.
15. Ahmed HU, El-Shater Bosaily A, Brown LC, et al. Diagnostic accuracy of mpMRI and targeted biopsy. Lancet. 2017; 389:815-22.
16. Kasivisvanathan V, et al. MRI-targeted biopsy vs standard TRUS biopsy. NEJM. 2018; 378:1767-77.
17. van der Leest M, et al. MRI-first pathway reduces biopsies. Lancet Oncol. 2019; 20:948-60.
18. Boesen L, et al. mpMRI diagnostic accuracy variability. Eur Urol Focus. 2022; 8:74-82.
19. Westphalen AC, et al. PI-RADS v2.1 performance. Radiology. 2021; 299:278-88.
20. Hansen NL, et al. PSAD thresholds improve PI-RADS 3 assessment. Eur Urol Oncol. 2021; 4:464-73.
21. Maggi M, et al. PSAD integration with mpMRI improves csPCa detection. Prostate Cancer Prostatic Dis. 2022; 25:1-9.
22. Loeb S, et al. PSA-based thresholds for biopsy. Eur Urol. 2014; 66:354-64.
23. Mottet N, et al. EAU Guidelines on Prostate Cancer. 2024 Edition.
24. NCCN Clinical Practice Guidelines in Oncology: Prostate Cancer. Version 2024.
25. Pilatz A, et al. Infection risk after TRUS biopsy. Eur Urol. 2020; 78:2-3.
26. Feliciano J, et al. Complications after transrectal biopsy. BJU Int. 2015; 116:173-9.
27. Briganti A, et al. Impact of prostate volume on the correlation between prostate-specific antigen level and prostate cancer detection. Eur Urol. 2007; 52:653-660.
28. Mehralivand S, et al. A grading system for extraprostatic extension on prostate MRI: detection and clinical outcomes. Radiology. 2019; 290:709-719.
29. Johnson LM, et al. Accuracy of multiparametric MRI for predicting extraprostatic extension in prostate cancer. AJR Am J Roentgenol. 2019; 213:W226-W235.
30. Taneja SS. Reconsidering nerve-sparing prostatectomy in MRIdefined extraprostatic extension. J Urol. 2018; 199:595-596.
31. Turkbey B, et al. Prostate Imaging Reporting and Data System version 2.1: 2019 update. Radiology. 2019; 292:400-403.
32. Park KJ, et al. PI-RADS category 3 lesions: cancer detection and management strategies. Urol Oncol. 2020; 38:573-582.
33. Sonn GA, et al. Targeted biopsy and misclassification in prostate cancer: limitations of MRI and TRUS biopsy. J Urol. 2013; 189:441-448.
34. Kasivisvanathan V, et al. MRI-targeted vs standard biopsy for prostate cancer detection: PRECISION trial. N Engl J Med. 2018;378:1767-1777.
35. Moldovan PC, et al. Accuracy of MRI and PI-RADS for prostate cancer detection: systematic review. Eur Urol. 2017; 72:896-913.
36. Schoots IG, et al. MRI in early prostate cancer detection: metaanalysis. Eur Urol. 2015; 67:627-636.
37. Lo Gullo R, et al. Role of PSA density in PI-RADS 3 lesions. Radiology. 2020; 296:343-351.
38. Washino S, et al. Optimal PSA density thresholds for detecting csPCa in PI-RADS 3 lesions. Urology. 2018; 113:92-96.
39. Nordström T, et al. PSA thresholds for biopsy referral: population- based study. Eur Urol. 2015; 68:123-130.
40. National Comprehensive Cancer Network (NCCN). Clinical Practice Guidelines in Oncology: Prostate Cancer. Version 2024.
41. European Association of Urology (EAU). Guidelines on Prostate Cancer. 2024 Edition.
42. Loeb S, et al. Systematic review of complications after prostate biopsy. Eur Urol. 2013; 64:876-892.
43. Ehdaie B, et al. Incidence of sepsis following prostate biopsy in contemporary practice. J Urol. 2014; 192:702-709.
44. Castellani D, Pirola GM, Xi Y, et al. Infection rate after transperineal prostate biopsy with and without prophylactic antibiotics: results from a systematic review and meta-analysis of comparative studies. J Urol. 2021; 207.
45. Grummet J, Gorin MA, Popert R, et al. Transperineal versus transrectal prostate biopsy: a prospective multicenter randomized trial. Lancet Infect Dis. 2022; 22:1191-1199.
46. Xiang J, Yan H, Li J, et al. Comparison of transrectal and transperineal prostate biopsy approaches for infection risk: a systematic review and meta-analysis. J Urol. 2022; 207:220-229.
47. Bianchi L, Gandaglia G, Fossati N, et al. Infectious complications after transrectal prostate biopsy in the era of targeted prophylaxis. BJU Int. 2023; 131:214-223.
48. Cho S, Jun DY, Lee JY, et al. Comparison of urinary tract infection rates between transperineal prostate biopsies with and without prophylactic antibiotics: an updated systematic review and metaanalysis. Medicina (Kaunas). 2025; 61:198.
49. Ma F, Zhang Y. Antibiotic prophylaxis may still be required among transperineal prostate biopsies in diabetic patients: a cohort study. Front Med. 2025; 12:1618631.
Ethics Approval
CRediT authorship contribution
Data collection and curation were performed by Walid Shanaa, and Ibrahim Alnadhari. Data analysis and interpretation were conducted by Ibrahim Alnadhari and Hana J. Abukhadijah. The initial draft of the manuscript was prepared by Walid Shanaa, Ibrahim Alnadhari, and Omar Ali with critical revision and intellectual input from all coauthors. Osama Abdeljaleel and Ahmad Shamsodini provided senior clinical oversight and supervision. All authors reviewed, approved the final version of the manuscript, and agreed to be accountable for all aspects of the work.
Supporting Agencies
Data Availability Statement
The data supporting the findings of this study are available from the corresponding author upon reasonable request.
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